The data literacy learning catalogue is organized by the step on the data journey and can be sorted by title, data competency, level, and type.
We have created a learning path that you can use as a guide to help you navigate your data literacy journey.
Data literacy learning catalogue
Title | Data journey | Competency | Level | Type |
|---|---|---|---|---|
An Introduction to the Data Journey Learn about the steps and activities in the data journey, which represents the key stages of the data process. | Foundation |
| Beginner | Video |
Analysis 101, part 1: Making an analytical plan Acquire a basic understanding of analysis and learn how to plan an analytical project. | Analyze – Model | Data analysis | Beginner | Video |
Analysis 101, part 2: Implementing the analytical plan Learn the best practices for implementing your analytical plan and perform the analysis. | Analyze – Model | Data analysis | Beginner | Video |
Analysis 101, part 3: Sharing your findings What are the best practices for interpreting and sharing your findings from an analytical project. | Analyze – Model | Data analysis | Beginner | Video |
Analysis 101, part 4: Case study Review the steps of the analytical process and obtain a better understanding of how analysts apply each step of the analytical process by walking through an example. | Analyze – Model | Data analysis | Beginner | Video |
Analysis 101: How to read a table Learn why data tables are important, how data tables are structured and how to interpret data quality indicators within a table. | Analyze – Model |
| Beginner | Video |
Assessing Data in a Time of Misinformation: A Step-by-Step Guide This job aid is designed to help you critically assess the data presented to you. | Foundation |
| Intermediate | Tool |
These videos are a reference source for users who are new to census concepts or those who have some experience with these concepts, but may need a refresher or would like to expand their knowledge. | Foundation |
| Beginner | Video |
Confidence Intervals Part 1: Uncertainty in Estimation Confidence intervals help us understand the uncertainty behind survey estimates. Learn about the three key components of a confidence interval: point estimates, margins of error, and confidence levels. | Analyze – Model |
| Intermediate | Video |
Confidence Intervals Part 2: Comparing Two Groups Discover how confidence intervals can be used to compare groups and assess whether observed differences are statistically meaningful. | Analyze – Model |
| Intermediate | Video |
Confidence Intervals Part 3: Factors Affecting the Width of a Confidence Interval Explore the three key factors that influence the width of a confidence interval: confidence level, population variability, and sample size. | Analyze – Model |
| Intermediate | Video |
Data Accuracy and Validation: Methods to ensure the quality of data Discover the methods to describe accuracy in terms of validity and correctness. | Explore – Clean – Describe |
| Beginner | Video |
Data ethics part 2: Ethical reviews What are ethical reviews? How do ethical reviews help Statistics Canada apply data ethics principles throughout the data journey? | Foundation |
| Intermediate | Video |
An introduction to data ethics, why they are important, and the 6 guiding principles of data ethics implemented by Statistics Canada. | Foundation |
| Beginner | Video |
Data Journey: What you need to know for successful navigation Learn about the steps and activities in the data journey, as well as the foundation supporting it. | Foundation |
| Beginner | Video |
Data Quality as Fitness for Use This course is intended for Government of Canada employees who would like to learn about evaluating the quality of data for a particular use. | Foundation | Evaluating data quality | Intermediate | Course |
Data quality in six dimensions An introduction to the fundamentals of data quality, which can be summed up in six dimensions—or six different ways to think about quality. Learn how each dimension can be used to evaluate the quality of data. | Foundation | Evaluating data quality | Beginner | Video |
This toolkit raises awareness about data quality assurance practices. | Foundation | Evaluating data quality | Intermediate | Tool |
Data Stewardship: An introduction Data gathering involves first determining what data you need, then where to find it, how to get it and how to keep it safe. Learn about things you should consider when gathering data. | Foundation | Data gathering | Beginner | Video |
Data Stewardship: An introduction to data standards and metadata Whether you're gathering new data or using existing data, applying data standards will make your life easier. And documenting your data in metadata will ensure that others will be able to find it, understand it, and use it. | Foundation |
| Beginner | Video |
Data Visualization Best Practices When used properly, charts (including figures and diagrams) can simplify the presentation of information and the communication of clear and precise messages. This reference tool provides a basic guide to creating effective charts that take advantage of the options available. | Tell the story |
| Intermediate | Publication |
Data Visualization: An Introduction An introductory overview of data visualization and how to use it to tell your story. | Tell the story |
| Beginner | Video |
FAIR data principles: What is FAIR? What does it means to be FAIR in terms of data and metadata, and how does each pillar of FAIR serve to guide data users and producers as they navigate their way through the data journey. | Foundation |
| Intermediate | Video |
In today's information environment, numbers can spread quickly, but not all data is collected or analyzed the same way. By thinking critically about data, you can avoid being misled to make smarter and more informed decisions. | Foundation |
| Beginner | Video |
Framework for Responsible Machine Learning Processes at Statistics Canada This document is a handbook for practitioners developing and implementing Machine Learning (ML) processes. It provides guidance and practical advice on how to responsibly develop these automated processes. | Analyze – Model |
| Intermediate | Publication |
Gathering Data: Things to Consider Before Gathering Data Data gathering involves first determining what data you need, then where to find it, how to get it and how to keep it safe. This video introduces you to things you should consider when gathering data. | Define – Find – Gather | Data gathering | Beginner | Video |
Machine learning: An introduction Welcome to machine learning: an introduction. Here, we will explain the basic concepts of machine learning, and include a framework for responsible machine learning processes. | Analyze – Model |
| Intermediate | Video |
Statistics 101: Confidence intervals What are confidence intervals? Why do we use confidence intervals? What factors have an impact on a confidence interval? | Foundation |
| Beginner | Video |
Statistics 101: Correlation and causality Gain a basic understanding of correlation and causality. | Analyze – Model |
| Intermediate | Video |
Statistics 101: Exploring measures of central tendency Acquire a basic understanding of the concept of central tendency, what it means and some key related methods used for the exploration of data. | Explore – Clean – Describe |
| Intermediate | Video |
Statistics 101: Exploring measures of dispersion Gain a basic understanding of such measures of dispersion as range, interquartile range, standard deviation. | Explore – Clean – Describe |
| Intermediate | Video |
Statistics 101: Proportions, ratios and rates An introduction to the concepts of proportions, ratios, and rates – and the differences between them. | Analyze – Model |
| Beginner | Video |
Statistics 101: Statistical Bias Learn about the concept of statistical bias, which occurs when statistics differ systematically from the reality they are trying to measure because of problems with the way the data were produced. | Explore – Clean – Describe |
| Intermediate | Video |
This web resource was created to assist secondary students and teachers in getting the most from statistics. | Foundation |
| Beginner | Publication |
Telling the data story: How to create stories that matter Learn how to tell interesting and informative stories with data. | Tell the story |
| Beginner | Video |
The Importance of Disaggregated Data: An Introduction (part 1) It can be very effective for all levels of governments and organizations that serve communities to use disaggregated data to make evidence-informed public policy decisions. | Foundation |
| Beginner | Video |
The Importance of Disaggregated Data: An Introduction (part 2) The use of disaggregated data can help policymakers to develop more targeted and effective policies by identifying the unique needs and challenges faced by different demographic groups. | Foundation |
| Beginner | Video |
Types of Data: Understanding and Exploring Data It is important to define the different types of data and understand them in order to choose the appropriate method for analyzing the data and presenting the results. | Explore – Clean – Describe | Data gathering | Beginner | Video |
Unlock the Power of Data Linkage Combining data from different sources can help address gaps in information, leading to better-informed policies and improved outcomes. Learn how data linkage can be used to gain deeper insights into various issues. | Explore – Clean – Describe |
| Intermediate | Video |
What is Data? An Introduction to Data Terminology and Concepts An introduction to some basic terminology and concepts related to data. | Foundation | Data awareness | Beginner | Video |
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